AUTHOR=Şen Hasan Tutkun, Cheng Alexis, Ding Kai, Boctor Emad, Wong John, Iordachita Iulian, Kazanzides Peter
TITLE=Cooperative Control with Ultrasound Guidance for Radiation Therapy
JOURNAL=Frontiers in Robotics and AI
VOLUME=3
YEAR=2016
PAGES=49
URL=https://www.frontiersin.org/article/10.3389/frobt.2016.00049
DOI=10.3389/frobt.2016.00049
ISSN=2296-9144
ABSTRACT=Radiation therapy typically begins with the acquisition of a CT scan of the patient for planning, followed by multiple days where radiation is delivered according to the plan. This requires that the patient be reproducibly positioned (set up) on the radiation therapy device (linear accelerator) such that the radiation beams pass through the target. Modern linear accelerators provide cone-beam computed tomography (CBCT) imaging, but this does not provide sufficient contrast to discriminate many abdominal soft-tissue targets and therefore patient setup is often done by aligning bony anatomy or implanted fiducials. Ultrasound (US) can be used to both assist with patient setup and to provide real-time monitoring of soft-tissue targets. One challenge, however, is that the ultrasound probe contact pressure can deform the target area and cause discrepancies with the treatment plan. Another challenge is that radiation therapists typically do not have ultrasound experience and therefore cannot easily find the target in the US image. We propose cooperative control strategies to address both challenges. First, we use cooperative control with virtual fixtures (VFs) to enable acquisition of a planning CT that includes the soft-tissue deformation. Then, for the patient setup during the treatment sessions, we propose to use real-time US image feedback to dynamically update the VFs; this co-manipulation strategy provides haptic cues that guide the therapist to correctly place the US probe. A phantom study is performed to demonstrate that the co-manipulation strategy enables inexperienced operators to quickly and accurately place the probe on a phantom to reproduce a desired reference image. This is a necessary step for patient setup and, by reproducing the reference image, creates soft-tissue deformations that are consistent with the treatment plan, thereby enabling real-time monitoring during treatment delivery.